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Tag Archive: sports science

  1. What the academics are keeping from the public

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    “The average number of readers of a scientific paper is…”

    before the beginningSir Martin Rees in his book “Before the beginning: our universe and others” discusses science, evidence and why information fails to get through to the public (Answer at the bottom of the page).

    University undergraduates are told by their lecturers that they must reference academic journals and that they need to be current. Books are less relevant as they are “out of date”. Naseem Taleb in “Antifragile” (a book) calls this “neomania“: the obsession with something new.

    Rees has this to say about journals:

    But these journals- what scientists call ‘the literature’– are impenetrable to non-specialists.  They now just exist for archival purposes, largely unread even by researchers, who depend more on informal ‘reprints’, email and conference.”

    Does that ring a bell for coaches who are wading through articles?

    Information distortion

    In the age of the tweet, the soundbite and 24 hr rolling news coverage, Rees explains that information can get distorted. Ben Goldacre talks about this in “Bad Science” where he postulates that science gets bad coverage due to the media being dominated by humanities students.

    Rees (the cynic) says “the distortion is even greater because some sceintists (and some institutions) are far more effective than others in communicating and promoting their researches.

    In the pseudoscience world, have you ever wondered why “power” is often narrowly defined by the ability to be tested on a force platform? Answer: where does most of the research come from? Which researcher is on the board of the company that makes the force platform?

    This power “research” is then disseminated as gospel (negative results are rarely published in journals, skewing the system further).

    Even if we see a well designed study, Rees suggests we bear in mind what Francis Crick has to say “no theory should agree with all the data, because some of the date are sure to be wrong!”

    Why we should ask difficult questions

    Francis bacon on learningOf course, we get what we deserve.  Francis Bacon said this in “The advancement of learning” (1605).

    “For as knowledges are now delivered, there is a kind of a contract of error between the deliverer and the receiver; for he that delivereth knowledge desireth to deliver it in such form as may be best believed, and not as may be best examined; and he that receiveth knowledge desireth rather present satisfaction than expectant inquiry.”

    Steve Myrland says that we believe our own fallibility more than the person presenting to us and that “those parts of presentations that are most confusing to us tend to be the parts we question least.”

    This then allows the “expert” to carry on building up an awe inspiring reputation that remains unchallenged.

    I see this a lot in pseudoscience journals from the UKSCA and NSCA: academics who have less coaching experience than our local primary school teachers are given platforms to promote their unfounded theories. Unfortunately those of us who coach have little time to write, let alone look at the references to check the validity of their claims.

    Thanks to Dr Rob Frost for lending me the book.

    Further reading:

    Answer: 0.6! (cynically, Rees wondered whether this included the referee).

  2. Bad Science

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    High pulls vs cleans

    High pulls

    Triple extension in the high pulls

    I was asked on Tuesday by an athlete who is quite new to weight lifting why I would teach cleans which are quite complex, if high pulls also work the triple extension.
    The answer is that I have got a lot of time with this athlete, so can afford to work on his technique without sacrificing his work that will lead to strength and power development. The clean will then enable him to perform the jerks without using a rack.

    But, the question is an excellent one, and should be asked by Coaches before they do any exercise or series of techniques, instead of doing something because everyone else is doing it.

    • Some National Governing Bodies specifically want cleans coached – why? If time is limited, then
    • dumbbell cleans
    •  jump squats
    • wave squats
    •  high pulls

    are all useful alternatives for developing power.

    Ben Goldacre’s Bad Science column in The Guardian is a good read and is an example of how to examine wild claims and pseudo science. This type of objectivity is uncommon in a lot of Coaching practice.

    It is especially interesting to read how the over complication of diet has led to a new brand of celebrity nutritionists who are being discredited due to their lack of scientific underpinning.

    I keep telling coaches and athletes that they should look at what they are trying to achieve, and find tools that do that job most efficiently.

    However, many people become attached to the “magic exercise” or “magic food” and then reverse engineer its usefulness to match the aims.

    Further reading:

  3. Improper Application and Interpretation of Sports Science Statistics

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    Juking the Stats: Why not all “research” is valid

    The latest craze in competitive sport appears to be the use of data to aid understanding of, and improvement in sporting performance. This has resulted in a glut of material, each item claiming to have established some new result which may have useful implications in the development and performance of human athletes.

    There are often studies conducted with non-athletes as well, and the line between what could be considered medical research as opposed to what is known as sports science is not clearly defined.

    I should stress that my knowledge of the field of sports science is limited, the purpose of this article is to question the structure and findings of some typical articles.

    A typical paper in this field might take the following form:

    1) Design a study with some hypothesis of interest
    2) Collect data from subjects (fitness testing)
    3) Analyse the data to check for consistency with the hypothesis
    4) Draw conclusions.

     A good statistician should be able to perform multiple roles.

    In my opinion, some of the most important are:

    1. To decide on the real questions at the heart of a problem of interest, not to just churn out results for the sake of it.
    2.  To decide if a hypothesis is necessary, and if so to construct one which is of real actual interest. Sometimes it is best to approach a problem with an open mind, in the knowledge that there are likely to be interesting results, but unsure of what they will be.
    3. To employ appropriate methods (typically statistical models) to analyse the collected data (we don’t need to get too technical here).
    4. To explain the underlying reasons behind any results – studies in which results are simply quoted as gospel are of limited interest to me.
    5. To critically review the work, pointing out potential shortcomings and areas for future research.

    The final point is perhaps the most interesting. It is often the role of a statistician to dampen (or in some cases pour cold water) on enthusiasm about some exciting results.

    Sports Science Statistics must be taken in context.

    Conclusions drawn from a study of, say, a weightlifter’s improved performance due to a certain type of training programme should not be used as an automatic basis for a different strength-based sport, such as rowing.

    I work in the field of weather forecasting. A modern-day weather forecast involves running a computer model forward in time to produce a single forecast of the atmosphere. Statistics of this forecast (such as the average forecast error) can be calculated at different locations. It is well-known that such statistics vary by location – it is more difficult to predict the weather in Shetland than in the Sahara Desert. We could not, therefore, use statistics derived from one location to predict the average forecast error in another.

    In short, statistics is about describing what might have happened in a given context, but didn’t. We can use these findings to issue probabilities of what might happen in the future, on the basis that the context is consistent.

    Forget the weather: what about sport science?

    The few articles I have read in the sports science field (in all honesty I couldn’t face reading too many!) seem to fall short on many of the above points.

    For example, Owen et al. (J Strength Cond Res, 2011) conduct a study of heart rate responses of soccer players when playing in three-sided and nine-sided games. They conclude that the HR of players in three-sided games is consistently higher than for nine-sided games. They also note that three-sided games provide more shooting chances, and encourage players to run more with the ball, whilst the nine-sided games produced more tackles, passes and interceptions.

    They draw the conclusions that three-sided games are preferable for fitness training, and suggest that strikers should participate in three-sided games whilst defenders should concentrate on nine-sided games.

    I have two main problems with this work from both a scientific and practical viewpoint.

    1. The statistics quoted in themselves should be treated with caution, given the small sample size of fifteen players who participated in only a few games of each type. Without conducting a formal test I cannot be more precise, but these measurements are undoubtedly subject to substantial variation.
    2. What insight does the study really offer us? Aren’t the findings, on which the entire article is based, merely confirmation of the obvious? It is useful here to consider the so-called `pyramid of outcomes’ .

    This study gives only surrogate measures (the base of the pyramid), but assumes in the conclusion that such surrogates automatically extend in to true performance measures (essentially whether they can be used to increase the probability of winning football matches).

    This assumption seems completely without foundation when one considers the practical implications of the study. For example, suppose that on the basis of the study, strikers train in three-sided games whilst defenders train in nine-sided games, in order to provide more shooting opportunities for strikers and more defending opportunities for defenders. Is there really any point in this? Wouldn’t three-sided games just result in strikers shooting from anywhere, and playing (by definition) against less able defensive opposition? Surely the way to improve as a striker is to learn how to play against good defenders?

    Frankly, this work smacks of conducting a study for the sake of it, and drawing conclusions based on a few surrogate measurements without paying any attention to the sport of interest.

    How to conduct a more informative study.

    1) Collect a larger sample of players from a variety of clubs, preferably from different countries.
    2) Train different groups of players in different environments, as suggested by the study.
    3) Collect surrogate measurements from the different training sessions.
    4) Examine if the surrogates had an effect on actual game results (i.e. construct a proper statistical model rather than merely reporting surrogate values).
    5) Examine whether a return to previous training routines result in a reversion to previous performance.

    A statistical model is essentially the use of surrogate measurements to aid in predicting the value of, and assessing the uncertainty in, measurements at the top of the pyramid. The article mentioned here simply assumes that larger surrogate values immediately imply improved results, an assertion which is without foundation.

    Such a study would admittedly be hard to carry out both practically and from a theoretical statistical viewpoint. However, we are dealing with complicated situations – we are essentially trying to model outcomes from the human body, an immensely complicated organism.

    This is my overriding point, studies which simply churn out results for the sake of publishing papers are of little practical use. I would go further and suggest that they are actually dangerous in the wrong hands – a statistical model is no good in the hands of an incapable operator.

    Conclusion

    From my brief consultation of the literature, I have seen many examples of a mis-use of statistics which would not be permitted in a statistics journal.

    The typical methods used are likely to underestimate the complexity of the situation at hand. I suspect therefore, that the true value of statistics such as the p-value are somewhat larger than reported.

    I feel confident in ascerting that the conclusions of the articles I have read are based on extremely shaky ground in a theoretical sense, let alone their practical shortcomings.

    Robin Williams Statistics Phd Student (University of Exeter),  England Blind Footballer, 2012 Olympian

    More on interpretation of data here 

  4. An Accurate Observation Is Never Wrong or What a Coach Needs to Know: Thomas Kurz

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    Tom Kurz

    First a statement from James Marshall’s book review of my book “Science of Sports Training”

    “The book is a bit old now, published in 2001, with most of the research quoted pre-dating that. This would probably disqualify it from being used as an academic text book, but as a Coaching handbook it is very good.”

    This made me think:

    “How important really is for a coach to have the most up-to-date research?”

    I quoted a lot of research papers in this book and in my other books. I did it to back up claims or advice that run contrary to common wisdom (or rather common stupidity…).

    Some of the old research I quoted was, and still is valuable no matter whether it was done in 1920 or in 2000. Human physiology (including its expression in human psychology) doesn’t change from decade to decade, not from century to century, hardly from millennium to millennium, so accurate observations of human nature hold true no matter their age. (Think the oldest medical manuals of India and China, or fencing manuals of ages past….)

    Valuable studies and experiments are those that reveal truths not likely arrived at by “listening to one’s body” or “paying attention to clues.” Everything else is just fulfilling the academic requirement to publish.

    What is important for a coach?

    Understanding human body and mind enough to know the relation between input and output, then observing athletes and adjusting the input. In one of my blog posts Training vs Skill Training or More on Super Slow and Similar Approaches, I wrote: “When in doubt, refer to everyday observations. An accurate observation is never wrong.”

    Take the most important, in my opinion, principle of sports training: The Principle of Individualization and Accessibility of Training. (When you think of it, all other principles of training are based on that one.) If you apply it, you see that studying the most recent research on exercise science matters much less than observing:

    • athletes’ mood
    • movement quality
    • signs of fatigue
    • signs of apprehension

    and adjusting training process accordingly.

    More articles on the practical application of principles of training are here and my observation-based posts are in my blog .

    Tom Kurz is the author of “Science of Sports Training.”

    Further reading:

  5. Exercise Physiology: Understanding the athlete within

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    “The performance of elite athletes is likely to defy the types of easy explanations sought by scientific reductionism.” (1)

    exercise physiology courseThe weak chink in my coaching armour (or the weakest link amongst many) is my exercise physiology knowledge. Having studied Italian at school instead of biology, I avoided Exercise Physiology subjects when doing my MSc.

    My coaching has been mainly with team sport or combat athletes and I have never felt the need to know more than the basics of physiology.

    However, when this course came up on Coursera, I took the opportunity to rectify this and see if I could help my current crop of athletes that include cyclists, modern pentathletes, marathoners and 1500m runners.

    Course outline

    Mark Hargreaves of Melbourne University set up the course with the aim that at the end of the course I would be able to:

    •describe the sequence of events in muscle contraction, the characteristics of skeletal muscle fibre types, their recruitment during exercise and relevance to athletic performance, the sites of energy use during muscle contraction and the specific muscle adaptations to different types of exercise.

    •  summarise the energy systems utilized during exercise of varying intensity and duration and understand the factors that influence carbohydrate and fat metabolism during exercise.

    •  describe the cardiorespiratory responses to exercise that facilitate oxygen delivery to, and consumption by, contracting skeletal muscle during exercise and summarise the physiological determinants of maximal oxygen uptake.

    •  understand the mechanisms of heat loss during exercise and their physiological implications, the effect of heat stress on physiological and metabolic responses to exercise and effective countermeasures, the effects of fluid loss on physiological function and the benefits of fluid replacement during exercise.

    •  describe the central and peripheral factors that mediate fatigue during exercise of varying intensity and duration and the physiological determinants of sprinting and endurance performance.

    •  appreciate the potential role of genetic factors in mediating exercise performance and responses to exercise training.

    There was a good mix of video lectures and journal articles to read. A pdf study guide also summarised the week’s learning with a very handy glossary. The 6 week course was punctuated by fortnightly quizzes, which counted towards the final mark.

    seb baylis A written assignment based on a case study of a collapsed Iron Man triathlete just before the finish line was peer reviewed. This has caused some consternation from other students as the marking has appeared a bit random.

    I got 18/20 on this section (I was tempted to write that he probably collapsed from boredom having listened to his fellow triathletes talk about their training…).

    The final exam was 25 multiple choice questions, some of which were quite tough.

     Key lessons

    The relationship between exercise duration and intensity is responsible for what energy substrates are used. An increase in ambient temperature also has an impact, with more carbohydrate being used.

    Repeated sessions in the heat leads to Carbohydrate depletion. However, the major cause of fatigue in the heat is the rise of core body temperature above 38C. This impedes blood flow and together with a fall in blood pressure, impedes the ability of the cv system to function as effectively.

    Delaying or limiting the rise in core temperature can therefore improve performance in the heat: acclimatisation, pre-cooling and fluid ingestion being the three main ways.

    The relationship between local and central fatigue was covered in some depth. Referring to Tim Noakes’ Central Governor Theory, I understood it more now than I did 15 years ago when I first saw him present on it.

    Fatigue could be “mind over muscle” with the mind protecting the body from damaging itself. However, experience, emotions and motivation can all influence this relationship.

    A couple of definitions also helped me clarify my thoughts:

    “Fatigue is a reduction in force and poer generating capacity”.

    “Fatigue is an inability to maintain the required or expected force or power output.” (Task failure).

    The diaphragm appears to be a clever piece of human kit. As a major part of our respiratory system, it works hard during maximal exercise (up to 15% of VO2 is used by it. When it fatigues a reflex signal occurs to the working muscles which limits motor activation.

    The sporting champion will come from a genetic pool of elite athletes. But, they need to work hard and maximise opportunities given to them in order to prevail.

    Summary and thoughts

    blood cells The course went into some detail about the cellular actions and I am doubtful as to whether knowing that GLUT4 is a glucose transport protein will help me or my athletes.

    The cellular physiology was hard work for me, and I doubt if I will remember the details in a month’s time.

    I am struggling to think of one change to my coaching practice that I will make as a result of this course.

    I gained lots of information, but little wisdom. The knowledge may impact on what I do in the future. It may have helped me understand the theory underpinning my exisitng practice. I return to the opening quote: being a coach means there is more to performance than what happens in the cells.

    Saying that, the quality of the information, the design of the course and how it was structured mean that it did what it said on the tin. I will be able to use a lot of this information on the coaching courses I deliver.

    Thanks to Professor Hargreaves and his team for setting it up. 

    If you want some other ideas for courses see Anatomy and Physiology courses

    This was my 5th MOOC following:

    • Crash Course in Creativity
    • Data Visualisation and Infographics
    • How Things Work
    • Inspiring Leadership Through Emnotional Intelligence

    Next up: “From the Big Bang to Dark Energy” (way out of my confort zone).

    References

    1 Joyner, M, Coyle F. The Journal of Physiology  Volume 586, Issue 1pages 35–44, January 2008